Preface xiii

1 Data and Case Studies 1

1.1 Case Study: Flight Delays 1

1.2 Case Study: BirthWeights of Babies 2

1.3 Case Study: Verizon Repair Times 3

1.4 Case Study: Iowa Recidivism 4

1.5 Sampling 5

1.6 Parameters and Statistics 6

1.7 Case Study: General Social Survey 7

1.8 Sample Surveys 8

1.9 Case Study: Beer and HotWings 9

1.10 Case Study: Black Spruce Seedlings 10

1.11 Studies 11

1.12 Google Interview Question: Mobile Ads Optimization 13

2 Exploratory Data Analysis 21

2.1 Basic Plots 21

2.2 Numeric Summaries 25

2.3 Boxplots 27

2.4 Quantiles and Normal Quantile Plots 29

2.5 Empirical Cumulative Distribution Functions 34

2.6 Scatter Plots 36

2.7 Skewness and Kurtosis 38

3 Introduction to Hypothesis Testing: Permutation Tests 45

3.1 Introduction to Hypothesis Testing 45

3.2 Hypotheses 46

3.3 Permutation Tests 50

3.4 Matched Pairs 66

3.5 Cause and Effect 67

4 Sampling Distributions 77

4.1 Sampling Distributions 77

4.2 Calculating Sampling Distributions 82

4.3 The Central LimitTheorem 85

5 Introduction to Confidence Intervals: The Bootstrap 103

5.1 Introduction to the Bootstrap 103

5.2 The Plug-in Principle 109

5.3 Bootstrap Percentile Intervals 115

5.4 Two Sample Bootstrap 116

5.5 Other Statistics 123

5.6 Bias 126

5.7 Monte Carlo Sampling 130

5.8 Accuracy of Bootstrap Distributions 131

5.9 How Many Bootstrap Samples Are Needed? 136

6 Estimation 147

6.1 Maximum Likelihood Estimation 147

6.2 Method of Moments 158

6.3 Properties of Estimators 160

6.4 Statistical Practice 174

7 More Confidence Intervals 183

7.1 Confidence Intervals for Means 183

7.2 Confidence Intervals Using Pivots 201

7.3 One-Sided Confidence Intervals 209

7.4 Confidence Intervals for Proportions 211

7.5 Bootstrap Confidence Intervals 216

7.6 Confidence Interval Properties 224

7.7 The Delta Method* 226

8 More Hypothesis Testing 245

8.1 Hypothesis Tests for Means and Proportions: One Population 245

8.2 Bootstrap t Tests 250

8.3 Hypothesis Tests for Means and Proportions: Two Populations 252

8.4 Type I and Type II Errors 261

8.5 Interpreting Test Results 276

8.6 Likelihood Ratio Tests 281

8.7 Statistical Practice 289

9 Regression 309

9.1 Covariance 309

9.2 Correlation 313

9.3 Least Squares Regression 316

9.4 The Simple LinearModel 329

9.5 Resampling Correlation and Regression 342

9.6 Logistic Regression 350

10 Categorical Data 367

10.1 Independence in Contingency Tables 367

10.2 Permutation Test of Independence 369

10.3 Chi-Square Test of Independence 371

10.4 Chi-Square Test of Homogeneity 380

10.5 Goodness-of-Fit Tests 382

10.6 Chi-Square and the Likelihood Ratio* 388

11 Bayesian Methods 399

11.1 Bayes Theorem 400

11.2 Binomial Data: Discrete Prior Distributions 400

11.3 Binomial Data: Continuous Prior Distributions 408

11.4 Continuous Data 414

11.5 Sequential Data 417

12 One-Way ANOVA 429

12.1 Comparing Three or More Populations 429

13 Additional Topics 443

13.1 S